Probe Travel Research Articles

A method for classifying the traffic states of signalized intersection using probe travel time

A method for classifying the traffic states of signalized intersection using probe travel time

Dimensionless squared jerk: An objective differential to assess experienced and novice probe movement in obstetric ultrasound.

ObjectiveWidely accepted, validated and objective measures of ultrasound competency have not been established for clinical practice. Outcomes of training curricula are often based on arbitrary thresholds, such as the number of clinical cases completed. We aimed to define metrics against which competency could be measured.MethodWe undertook a prospective, observational study of obstetric sonographers at a UK University Teaching Hospital. Participants were either experienced in fetal ultrasound (n = 10, >200 ultrasound examinations) or novice operators (n = 10, <25 ultrasound examinations). We recorded probe motion data during the performance of biometry on a commercially available mid‐trimester phantom.ResultsWe report that Dimensionless squared jerk, an assessment of deliberate hand movements, independent of movement duration, extent, spurious peaks and dimension differed significantly different between groups, 19.26 (SD 3.02) for experienced and 22.08 (SD 1.05, p = 0.01) for novice operators, respectively. Experienced operator performance, was associated with a shorter time to task completion of 176.46 s (SD 47.31) compared to 666.94 s (SD 490.36, p = 0.0004) for novice operators. Probe travel was also shorter for experienced operators 521.23 mm (SD 27.41) versus 2234.82 mm (SD 188.50, p = 0.007) when compared to novice operators.ConclusionOur results represent progress toward an objective assessment of technical skill in obstetric ultrasound. Repeating this methodology in a clinical environment may develop insight into the generalisability of these findings into ultrasound education.

Data Processing Techniques for Real-Time Traveler Information: Use of Dedicated Short-Range Communications Probes on Suburban Arterial

Background:As wireless communication technologies evolve, probe-based travel-time collection systems are becoming popular around the globe. However, two problems generally arise in probe-based systems: one is the outlier and the other is time lag. To resolve the problems, methods for outlier removal and travel-time prediction need to be applied.Methods:In this study, data processing methods for addressing the two issues are proposed. After investigating the characteristic of the travel times on the test section, the modified z-score was suggested for censoring outliers contained in probe travel times. To mitigate the time-lag phenomenon, a recurrent neural network, a class of deep learning where temporal sequence data are normally treated, was applied to predict travel times.Results:As a result of evaluation with ground-truth data obtained through test-car runs, the proposed methods showed enhanced performances with prediction errors lower than 13% on average compared to current practices.Conclusion:The suggested methods can make drivers to better arrange their trip schedules with real-time travel-time information with improved accuracy.

Estimation of Performance Metrics at Signalized Intersections Using Loop Detector Data and Probe Travel Times

This paper introduces a simple but practical approach that uses both loop detector data and probe travel times for computing the vehicle hours traveled (VHT), average delay, and level of service (LOS) for signalized intersections. The goal is to improve upon the state-of-the-practice method outlined in the highway capacity manual (HCM) by incorporating additional travel time measurements from probe vehicles or vehicle re-identification systems. The proposed methodology is designed to work under a variety of traffic conditions, including states of congestion in which the HCM methodology is not reliable. Our analysis is then tested using simulation of an arterial site in Arcadia, CA, USA. The results suggest that the proposed methodology performs better at the approach level than at the lane group level. Population size and probe penetration rate are two key parameters in the estimation. Either a large population size or a high penetration rate is required in order to produce reliable estimates of VHT, delay, and LOS. Results also show that the proposed methodology only requires 7% of the penetration rate to outperform the HCM methodology.

An Improved Ant Colony Algorithm for Optimal Path of Travel Research and Simulation

Tourist travel path’s unseemliness will result in serious of problems, such as expenses, comfort level, travel safety, etc. This paper analyzed the NP hard problem of travel optimal path, proposed an improved ant colony algorithm. Firstly, distance matrix was constructed, the travel spots’ initial order were represented by subscript randomly. Secondly, the path choose model was proposed by travel example, and analyzed the simulation result based on the improved ant colony algorithm; Finally, this paper analyzed the influence of parameters with path result, the simulation result proved the validity of the algorithm, which could plan the travel path reasonably, would assist travel agency to formulate probe travel strategy, and improved the travel cost and traffic for tourist

Application of High-Resolution Vehicle Data for Free-Flow Speed Estimation

The use of probe vehicle data for highway performance monitoring is increasingly being adopted in many countries. In the United States, third-party data provider entities such as Google, INRIX, HERE, and TomTom are delivering products to state and local transportation agencies that are enabling them to identify bottlenecks, incidents, and other key operational events on the basis of probe vehicle speed and travel time. However, the capacity analysis methods in the U.S. Highway Capacity Manual continue, for the most part, to rely on the analyst’s ability to gather data at fixed points, whether manually or from fixed point sensors. This paper explores the use of intelligence to drive (i2D) high-resolution vehicle data to assess several research questions related to free-flow speed (FFS) estimation, a key parameter in freeway segment analyses. On the basis of 1 year of high-resolution data collected from a local fleet of about 20 vehicles driven by volunteer drivers, researchers accumulated more than 20 million s of driving, which when filtered were used to evaluate research questions and develop enhanced predictive models for FFS. Speed limit and section ramp density (i.e., those ramps within the segment proper only) were found to have had a strong effect on the value of FFS. Driver familiarity was found to have an effect also, although this effect was not conclusive across 10 study sites. Finally, an FFS predictive model that incorporates speed limit and section ramp density was found to fit the high-resolution data quite well, generating an absolute error of only 1.3% across all sites. That finding compares with an error of 6.6% with the current Highway Capacity Manual 2010 model predictions.

Probe localization for freehand 3D ultrasound by tracking skin features.

Ultrasound probe localization with respect to the patient's body is essential for freehand three-dimensional ultrasound and image-guided intervention. However, current methods for probe localization generally involve bulky and expensive equipment. In this paper, a highly cost-effective and miniature-mobile system is described for 6-DoF probe localization that is robust to rigid patient motion. In this system, skin features in the scan region are recorded at each ultrasound scan acquisition by a lightweight camera rigidly mounted to the probe. A skin map is built based on the skin features and optimal probe poses are estimated in a Bayesian probabilistic framework that incorporates a prior motion model, camera frames, and ultrasound scans. Through freehand scanning on three different body parts, it is shown that on average, for every probe travel distance of 10 mm, the translational and rotational errors are 0.91 ± 0.49 mm and 0.55 degrees ± 0.17 degrees, respectively. The 3D reconstructions were also validated by comparison with real ultrasound scans.

Short-Term Travel Time Prediction Using the Kalman Filter Combined with a Variable Aggregation Interval Scheme

Data aggregation interval is important for reliable travel time predictions in probe-based systems. Where sufficient probes exist, a short interval can be used to minimize the time delay. However, in the opposite case, a short interval can cause unreliable travel time predictions due to small probes. Thus, the optimal aggregation interval may vary according to traffic flow conditions. This study suggests a methodology for selecting the optimal aggregation interval which varies according to a characteristic of probe travel time. The superiority of the proposed methodology compared to a conventional fixed interval is verified using DSRC probe data collected on a multilane highway near Seoul, Korea. The Kalman filter is adopted for a travel time prediction technique. As a consequence, the prediction accuracy is enhanced by approximately 40% compared to a fixed aggregation interval under free flow conditions.

Supporting large-scale travel surveys with smartphones – A practical approach

Collection of travel data is a key task of transportation modeling. Data collection is currently based on costly and time-intensive questionnaires, and can thus only provide limited cross-sectional coverage and inadequate updates. There is an urgent need for technologically supported travel data acquisition tools. We present a novel approach for supporting travel surveys using data collected with smartphones. Individual trips of the person carrying the phone are automatically reconstructed and trip legs are classified into one of eight different modes of transport. This task is performed by an ensemble of probabilistic classifiers combined with a Discrete Hidden Markov Model (DHMM). Classification is based on features extracted from the motion trajectory recorded by the smartphone’s positioning system and signals of the embedded accelerometer. Our approach can cope with GPS signal losses by including positioning data obtained from the mobile phone cell network, and relies solely on accelerometer features when the trajectory cannot be reconstructed with sufficient accuracy. To train and evaluate the models, 355h of probe travel data were collected in the metropolitan area of Vienna, Austria by 15 volunteers over a period of 2months. Distinguishing eight different transportation modes, the classification results range from 65% (train, subway) to 95% (bicycle). The increasing popularity of smartphones gives the proposed method the potential to be used on a wide-spread basis and can complement existing travel survey methods.

Turning Rate Estimation at a Signalized Intersection Using Probe Data

Knowing the turning rates at an intersection can contribute to the improvement of signal control parameters and correct estimation of vehicle delays. This study proposes a methodology for estimating turning rates at an intersection under oversaturated traffic conditions. Data from detectors and infrared beacons (probe data) are used with a traffic simulator to reproduce average probe travel times for different turning ratio values. Turning rates were estimated by observing the change in the parameters describing the linear relationship between the entry time and average probe travel time for different turning rates and comparing them with the values from virtual probe and detector data. The methodology works well with simulated data.

A three dimensional probe positioner

In order to sort out the physics that is important in many plasma experiments, data in three dimensions (3D) are becoming necessary. Access to the usual cylindrical vacuum vessel is typically restricted to radially or axially insertable probes that can pivot. The space that can be explored usually has significant restrictions either because probe travel must be along a travel path, or a "wobbly" probe positioner requires one to map between a moveable coordinate system and a preferred laboratory coordinate system. This could for example introduce errors in measurements of vector quantities such as magnetic field or flow. We describe the design and implementation of a 3D probe positioner that slides in two dimensions on a double O-ring seal and radially inserts along the third dimension. The net result is that a 3D space can be explored in a laboratory Cartesian reference frame.

Developments in ultrashallow spreading resistance analysis

Spreading resistance analysis on ultrashallow structures is complicated by the interaction of bevel rounding with geometric effects associated with lateral boundaries. When a spreading resistance probe is stepped from the original sample surface, across the rounded region at the bevel edge and onto the bevel, the resistance increases. Some of the increase is the result of approaching the lateral boundary represented by the bevel, and some is the result of increasing local sheet resistance as the probes begin to move below the original surface. We remove the geometric effect by solving the boundary value problem involving a sheet resistance which varies with distance along the direction of probe travel. Having obtained the local sheet resistance, we assign a depth for each point from profilometer data, and the usual depth-dependent analysis is used to obtain the resistivity profile.

Multi-state and multi-sensor incident detection systems for arterial streets

Incident detection systems typically emphasize incident presence and location over incident severity and incident recovery. Yet, Advanced Traveller Information Systems (ATIS) and Advanced Traffic Management Systems (ATMS) rely on the latter states to implement and terminate diversion, and its supportive control strategies. Further, incident detection systems directly benefit from processing measurement vectors rather than scalars. Vectors of lane measurements favor detection through lane imbalances and identification of incident host lanes. Intelligent Transportation Systems promise new sensor data to control centers, including the travel times experienced by probe vehicles. Vectors of new and old sensor inputs may possess enhanced discriminatory values. To accomodate added detection states and the fusion of multi-sensor input vectors, this paper reformulates the arterial incident detection problem as a multiple attribute decision making problem with Bayesian scores. This novel approach utilizes as input the combinations of simulated probe travel times, number of probe reports, lane specific detector occupancies and vehicle counts. Models based solely on probe data lack in performance due to excessive overlaps in class distributions. Models based on detector occupancies and vehicle counts by lane perform outstandingly. They display a propensity to detect through lane measurement imbalances. The probe data is shown to enhance the performance of detector data based models.

Simulation of an Arterial Incident Environment with Probe Reporting Capability

Intelligent transportation systems have created new traffic monitoring approaches and fueled new interests in automated incident detection systems. One new monitoring approach utilizes actual travel times experienced by vehicles, called probes, equipped to transmit this information in real time to a control center. The database needed to design and calibrate arterial incident detection systems based on probe travel times is nonexistent. A microscopic traffic simulation package, Integrated Traffic Simulation, was selected and enhanced to generate vehicle travel times for the incident and incident-free conditions on an arterial. We evaluated the enhanced model. Significant variations in probe travel times were observed in the event of incidents. Average travel time, contrary to average occupancy, may increase, decrease, or remain constant on arterial streets downstream of an incident.

Frequency of Probe Reports and Variance of Travel Time Estimates

An important design issue relating to probe-based Advanced Traveler Information Systems (ATISs) and Advanced Traffic Management systems is the sample size of probes (or the number of link traversals by probe vehicles) per unit time used in order to obtain reliable network information in terms of link travel time estimates. The variance of the mean of travel times obtained from n probes for the same link over a fixed time period may be shown to be of the form a+b/n where a and b are link-specific parameters. Using probe travel time data from a set of signalized arterials, it is shown that a is positive for well-traveled signalized links. This implies that the variance does not go to zero with increasing n. Consequences of this fact for probe-based systems are explored. While the results presented are for a specific set of links, the authors argue that because of the nature of the underlying travel time process, the broad conclusions would not hold for most well-traveled links with signal control.

Internal toroidal field measurements on the helicity injected tokamak using the transient internal probe

Measurements of the local toroidal magnetic field have been achieved on the helicity injected tokamak (HIT) using the transient internal probe (TIP). HIT is a low aspect (a=1.5, R=0.35 m) ratio tokamak designed to study steady state current drive. The TIP diagnostic involves accelerating a small diamond clad magneto-optic probe through the plasma at high velocities (∼2 km/s) using a light gas gun. The local field is obtained by illuminating the probe with a laser and measuring the amount of Faraday rotation in the reflected beam. Measurements were conducted using unclad magneto-optic probes directed along a chord tangent to the toroidal field. Plasma conditions were typically ne∼7×1019 m−3 and Te∼40–80 eV. Measurement uncertainty is less than 2%. No changes in plasma parameters were observed during the first 200 ms (∼40 cm) of probe travel in the plasma. A temporary dip in plasma current, probably due to ablation of the retroreflecting material on the probe, is observed as the probe exits the plasma. Density is unaffected by the presence of the probe in the plasma. No long term deleterious effects to tokamak performance were observed as the TIP diagnostic was found to be quite compatible with the tokamak.

Using Probe-Measured Travel Times to Detect Major Freeway Incidents in Houston, Texas

As a prelude to installing an automatic vehicle identification system for collecting traffic and travel time information from probe vehicles, the Texas Transportation Institute, in conjunction with the Texas Department of Transportation, initiated a pilot study to test the feasibility of using probe-provided travel time information to detect freeway incidents. As part of this pilot study, 200 commuters equipped with cellular telephones were used to collect travel time and incident information from three facilities [I-45 (both the main lanes and the high-occupancy-vehicle lane), the Hardy Toll Road, and US-59] on the north side of Houston, Texas. Historical travel time patterns were developed for each link using data from known incident-free conditions. The statistical principle of standard normal deviates was applied to 11 months of data to determine when a probe travel time exceeded the expected travel time under incident-free conditions. Whereas this approach resulted in detection rates that were lower and false alarm rates that were higher than those reportedly produced by other incident detection algorithms, this study illustrated that some level of incident detection could be achieved using travel time information provided by probe vehicles. Because of limitations in the data, it was not possible to determine the number of incidents that were not detected by the system or the detection times for the known incident conditions.

Using Probe-Measured Travel Times to Detect Major Freeway Incidents in Houston, Texas

As a prelude to installing an automatic vehicle identification system for collecting traffic and travel time information from probe vehicles, the Texas Transportation Institute, in conjunction with the Texas Department of Transportation, initiated a pilot study to test the feasibility of using probe-provided travel time information to detect freeway incidents. As part of this pilot study, 200 commuters equipped with cellular telephones were used to collect travel time and incident information from three facilities [I-45 (both the main lanes and the high-occupancy-vehicle lane), the Hardy Toll Road, and US-59] on the north side of Houston, Texas. Historical travel time patterns were developed for each link using data from known incident-free conditions. The statistical principle of standard normal deviates was applied to 11 months of data to determine when a probe travel time exceeded the expected travel time under incident-free conditions. Whereas this approach resulted in detection rates that were lower and false alarm rates that were higher than those reportedly produced by other incident detection algorithms, this study illustrated that some level of incident detection could be achieved using travel time information provided by probe vehicles. Because of limitations in the data, it was not possible to determine the number of incidents that were not detected by the system or the detection times for the known incident conditions.

Evaluation of the Gamma and Neutron Radiation Scattering and Transmission Methods for Soil Density and Moisture Determination

Abstract In order to warrant the accuracy of soil density and moisture data from measurements by means of the gamma and neutron radiation attenuation methods several influencing factors have to be taken into account, for example, the soil hydrogen content, the soil inhomogeneity, the resolution characteristics of the measuring device and the probe travel velocity. Some interpretation concepts, related to the total hydrogen content in soil, are discussed in view of a calibration protocol. An iterative calculation procedure is proposed for the case of saturated soil, especially for the case that local organic content information is lacking. Further, a probe-travel velocity criterion and a possible approach to increase the resolution of a measured density profile are presented. Interpretation problems associated with data from inhomogeneous soil, measured with different devices, are discussed in relation with the difference in spatial averaging characteristics, which influence the significance of the measured quantity.

Laboratory tests of a motorized snow surface hardness gage

A motor-driven, spherical probe controlled by a handheld calculator and a microprocessor developed to measure the force and probe travel distance needed to break individual snow surface elements was tested for consistency and reliability. Consistency tests were run on automatic pencil leads; reliability tests on ice rods. Both proved satisfactory. Tests on two man-made snow surfaces showed the probe capable of measuring the strength of individual snow surface elements. Brittle failure occurred in such elements at loads varying from 0.200 to 174.631 grams (median 11.560 grams) for 118 samples. Probe travel distance varied from 0.003 to 0.099 mm (median 0.017 mm). The load needed to cause the first break was less than 1 gram for 21 (18%) of the samples.